Abstract: With the explosive growth of data available on the
Internet, personalization of this information space become a
necessity. At present time with the rapid increasing popularity of the
WWW, Websites are playing a crucial role to convey knowledge and
information to the end users. Discovering hidden and meaningful
information about Web users usage patterns is critical to determine
effective marketing strategies to optimize the Web server usage for
accommodating future growth. The task of mining useful information
becomes more challenging when the Web traffic volume is enormous
and keeps on growing. In this paper, we propose a intelligent model
to discover and analyze useful knowledge from the available Web
log data.
Abstract: This paper emphasizes on the application of genetic algorithm (GA) to optimize the parameters of the TMD for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using GA that has a story ability to find the most optimistic results. An 11–story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed GA based TMD (GATMD) controller without specifying which mode should be controlled. The results of the proposed GATMD controller are compared with the uncontrolled structure through timedomain simulation and some performance indices. The results analysis reveals that the designed GA based TMD controller has an excellent capability in reduction of the seismically excited example building and the ITAE performance, that is so for remains as unknown, can be introduced a new criteria - method for structural dynamic design.
Abstract: In this paper we propose a Particle Swarm heuristic
optimized Multi-Antenna (MA) system. Efficient MA systems
detection is performed using a robust stochastic evolutionary
computation algorithm based on movement and intelligence of
swarms. This iterative particle swarm optimized (PSO) detector
significantly reduces the computational complexity of conventional
Maximum Likelihood (ML) detection technique. The simulation
results achieved with this proposed MA-PSO detection algorithm
show near optimal performance when compared with ML-MA
receiver. The performance of proposed detector is convincingly
better for higher order modulation schemes and large number of
antennas where conventional ML detector becomes non-practical.
Abstract: Most agricultural crops cultivated in Brazil are highly
nutrient demanding. Brazilian soils are generally acidic with low base
saturation and available nutrients. Demand for fertilizer application
has increased because the national agricultural sector expansion. To
improve productivity without environmental impact, there is the need
for the utilization of novel procedures and techniques to optimize
fertilizer application. This includes the digital soil mapping and GIS
application applied to mapping in different scales. This paper is
based on research, realized during 2005 to 2010 by Brazilian
Corporation for Agricultural Research (EMBRAPA) and its partners.
The purpose was to map soil fertility in national and regional scales.
A soil profile data set in national scale (1:5,000,000) was constructed
from the soil archives of Embrapa Soils, Rio de Janeiro and in the
regional scale (1:250,000) from COMIGO Cooperative soil data set,
Rio Verde, Brazil. The mapping was doing using ArcGIS 9.1 tools
from ESRI.
Abstract: Most integrated inertial navigation systems (INS) and
global positioning systems (GPS) have been implemented using the
Kalman filtering technique with its drawbacks related to the need for
predefined INS error model and observability of at least four
satellites. Most recently, a method using a hybrid-adaptive network
based fuzzy inference system (ANFIS) has been proposed which is
trained during the availability of GPS signal to map the error
between the GPS and the INS. Then it will be used to predict the
error of the INS position components during GPS signal blockage.
This paper introduces a genetic optimization algorithm that is used to
update the ANFIS parameters with respect to the INS/GPS error
function used as the objective function to be minimized. The results
demonstrate the advantages of the genetically optimized ANFIS for
INS/GPS integration in comparison with conventional ANFIS
specially in the cases of satellites- outages. Coping with this problem
plays an important role in assessment of the fusion approach in land
navigation.
Abstract: Short message integrated distributed monitoring systems (SM-DMS) are growing rapidly in wireless communication applications in various areas, such as electromagnetic field (EMF) management, wastewater monitoring, and air pollution supervision, etc. However, delay in short messages often makes the data embedded in SM-DMS transmit unreliably. Moreover, there are few regulations dealing with this problem in SMS transmission protocols. In this study, based on the analysis of the command and data requirements in the SM-DMS, we developed a processing model for the control center to solve the delay problem in data transmission. Three components of the model: the data transmission protocol, the receiving buffer pool method, and the timer mechanism were described in detail. Discussions on adjusting the threshold parameter in the timer mechanism were presented for the adaptive performance during the runtime of the SM-DMS. This model optimized the data transmission reliability in SM-DMS, and provided a supplement to the data transmission reliability protocols at the application level.
Abstract: Density functional theory (DFT) calculations were performed to calculate aluminum-27, boron-11, and nitrogen-14 quadrupole coupling constant (CQ) in the representative considered model of (6, 0) boron nitride-aluminum nitride nanotube junction (BN-AlNNT) for the first time. To this aim, 1.3 nm length of BNAlN consisting of 18 Al, 18 B, and 36 N atoms was selected where the end atoms capped by hydrogen atoms. The calculated CQ values for optimized BN-AlNNT system reveal different electrostatic environment in the mentioned system. The calculations were performed using the Gaussian 98 package of program.
Abstract: Functioning of a biometric system in large part
depends on the performance of the similarity measure function.
Frequently a generalized similarity distance measure function such as
Euclidian distance or Mahalanobis distance is applied to the task of
matching biometric feature vectors. However, often accuracy of a
biometric system can be greatly improved by designing a customized
matching algorithm optimized for a particular biometric application.
In this paper we propose a tailored similarity measure function for
behavioral biometric systems based on the expert knowledge of the
feature level data in the domain. We compare performance of a
proposed matching algorithm to that of other well known similarity
distance functions and demonstrate its superiority with respect to the
chosen domain.
Abstract: A simple analytical model has been developed to
optimize biasing conditions for obtaining maximum linearity among
lattice-matched, pseudomorphic and metamorphic HEMT types as
well as enhancement and depletion HEMT modes. A nonlinear
current-voltage model has been simulated based on extracted data to
study and select the most appropriate type and mode of HEMT in
terms of a given gate-source biasing voltage within the device so as
to employ the circuit for the highest possible output current or
voltage linear swing. Simulation results can be used as a basis for the
selection of optimum gate-source biasing voltage for a given type
and mode of HEMT with regard to a circuit design. The
consequences can also be a criterion for choosing the optimum type
or mode of HEMT for a predetermined biasing condition.
Abstract: This paper proposes a fast tree join scheme to provide
seamless multicast handover in the mobile networks based on the Fast
Mobile IPv6 (FMIPv6). In the existing FMIPv6-based multicast
handover scheme, the bi-directional tunnelling or the remote
subscription is employed with the packet forwarding from the previous
access router (AR) to the new AR. In general, the remote subscription
approach is preferred to the bi-directional tunnelling one, since in the
remote subscription scheme we can exploit an optimized multicast
path from a multicast source to many mobile receivers. However, in
the remote subscription scheme, if the tree joining operation takes a
long time, the amount of data packets to be forwarded and buffered for
multicast handover will increase, and thus the corresponding buffer
may overflow, which results in severe packet losses. In order to reduce
these costs associated with packet forwarding and buffering, this paper
proposes the fast join to multicast tree, in which the new AR will join
the multicast tree as fast as possible, so that the new multicast data
packets can also arrive at the new AR, by which the packet forwarding
and buffering costs can be reduced. From numerical analysis, it is
shown that the proposed scheme can give better performance than the
existing FMIPv6-based multicast handover schemes in terms of the
multicast packet delivery costs.
Abstract: The proposed Multimedia Pronunciation Learning
Management System (MPLMS) in this study is a technology with
profound potential for inducing improvement in pronunciation
learning. The MPLMS optimizes the digitised phonetic symbols with
the integration of text, sound and mouth movement video. The
components are designed and developed in an online management
system which turns the web to a dynamic user-centric collection of
consistent and timely information for quality sustainable learning.
The aim of this study is to design and develop the MPLMS which
serves as an innovative tool to improve English pronunciation. This
paper discusses the iterative methodology and the three-phase Alessi
and Trollip model in the development of MPLMS. To align with the
flexibility of the development of educational software, the iterative
approach comprises plan, design, develop, evaluate and implement is
followed. To ensure the instructional appropriateness of MPLMS, the
instructional system design (ISD) model of Alessi and Trollip serves
as a platform to guide the important instructional factors and process.
It is expected that the results of future empirical research will support
the efficacy of MPLMS and its place as the premier pronunciation
learning system.
Abstract: Despite the availability of natural disaster related time series data for last 110 years, there is no forecasting tool available to humanitarian relief organizations to determine forecasts for emergency logistics planning. This study develops a forecasting tool based on identifying probability distributions. The estimates of the parameters are used to calculate natural disaster forecasts. Further, the determination of aggregate forecasts leads to efficient pre-disaster planning. Based on the research findings, the relief agencies can optimize the various resources allocation in emergency logistics planning.
Abstract: This paper proposes a new design of spatial FIR
filter to automatically detect water level from a video signal of
various river surroundings. A new approach in this report applies
"addition" of frames and a "horizontal" edge detector to distinguish
water region and land region. Variance of each line of a filtered
video frame is used as a feature value. The water level is recognized
as a boundary line between the land region and the water region.
Edge detection filter essentially demarcates between two distinctly
different regions. However, the conventional filters are not
automatically adaptive to detect water level in various lighting
conditions of river scenery. An optimized filter is purposed so that
the system becomes robust to changes of lighting condition. More
reliability of the proposed system with the optimized filter is
confirmed by accuracy of water level detection.
Abstract: Service identification is one of the main activities in
the modeling of a service-oriented solution, and therefore errors
made during identification can flow down through detailed design
and implementation activities that may necessitate multiple
iterations, especially in building composite applications. Different
strategies exist for how to identify candidate services that each of
them has its own benefits and trade offs. The approach presented in
this paper proposes a selective identification of services approach,
based on in depth business process analysis coupled with use cases
and existing assets analysis and goal service modeling. This article
clearly emphasizes the key activities need for the analysis and
service identification to build a optimized service oriented
architecture. In contrast to other approaches this article mentions
some best practices and steps, wherever appropriate, to point out the
vagueness involved in service identification.
Abstract: QoS Routing aims to find paths between senders and
receivers satisfying the QoS requirements of the application which
efficiently using the network resources and underlying routing
algorithm to be able to find low-cost paths that satisfy given QoS
constraints. The problem of finding least-cost routing is known to be
NP-hard or complete and some algorithms have been proposed to
find a near optimal solution. But these heuristics or algorithms either
impose relationships among the link metrics to reduce the complexity
of the problem which may limit the general applicability of the
heuristic, or are too costly in terms of execution time to be applicable
to large networks. In this paper, we concentrate an algorithm that
finds a near-optimal solution fast and we named this algorithm as
optimized Delay Constrained Routing (ODCR), which uses an
adaptive path weight function together with an additional constraint
imposed on the path cost, to restrict search space and hence ODCR
finds near optimal solution in much quicker time.
Abstract: The latest Geographic Information System (GIS)
technology makes it possible to administer the spatial components of
daily “business object," in the corporate database, and apply suitable
geographic analysis efficiently in a desktop-focused application. We
can use wireless internet technology for transfer process in spatial
data from server to client or vice versa. However, the problem in
wireless Internet is system bottlenecks that can make the process of
transferring data not efficient. The reason is large amount of spatial
data. Optimization in the process of transferring and retrieving data,
however, is an essential issue that must be considered. Appropriate
decision to choose between R-tree and Quadtree spatial data indexing
method can optimize the process. With the rapid proliferation of
these databases in the past decade, extensive research has been
conducted on the design of efficient data structures to enable fast
spatial searching. Commercial database vendors like Oracle have also
started implementing these spatial indexing to cater to the large and
diverse GIS. This paper focuses on the decisions to choose R-tree
and quadtree spatial indexing using Oracle spatial database in mobile
GIS application. From our research condition, the result of using
Quadtree and R-tree spatial data indexing method in one single
spatial database can save the time until 42.5%.
Abstract: Presently and in line with the United Nations (EPA),
human thinking system has shifted towards clean fuels so as to
maintain a cleaner environment and to save our planet earth.
One of the most successful studies in order to achieve new
energies includes the use of animal wastes and their organic residues,
and the result of these researches has been represented in the form of
very simple and cheap methods called biogas technology. Biogas
technology has developed a lot in the recent decades; its reason is the
high cost of fossil fuels and the greater attention of countries to the
environmental pollutions due to the consumption of this kind of
fuels.
IRAN is ready for the optimized application of renewable
energies, having much enriched resources of this kind of energies; so
a special place could be considered for it when making programs.
The purpose of biogas technology is the recovery of energy and
finally the protection of the environment, which is much appropriate
for the third world farmers with respect to their technical abilities and
economic potentials. Studies show that the production and
consumption of biogas is appropriate and economic in IRAN,
because of the high amount of waste in the agriculture sector, the
significant amount of animal and human excrement production, the
great volume of garbage produced and the most important the
specific social, climatic and agricultural conditions in IRAN, in order
to proceed towards the reduction of pollution due to the use of fossil
fuels.
Abstract: Multiplication algorithms have considerable effect on
processors performance. A new high-speed, low-power
multiplication algorithm has been presented using modified Dadda
tree structure. Three important modifications have been implemented
in inner product generation step, inner product reduction step and
final addition step. Optimized algorithms have to be used into basic
computation components, such as multiplication algorithms. In this
paper, we proposed a new algorithm to reduce power, delay, and
transistor count of a multiplication algorithm implemented using low
power modified counter. This work presents a novel design for
Dadda multiplication algorithms. The proposed multiplication
algorithm includes structured parts, which have important effect on
inner product reduction tree. In this paper, a 1.3V, 64-bit carry hybrid
adder is presented for fast, low voltage applications. The new 64-bit
adder uses a new circuit to implement the proposed carry hybrid
adder. The new adder using 80 nm CMOS technology has been
implemented on 700 MHz clock frequency. The proposed
multiplication algorithm has achieved 14 percent improvement in
transistor count, 13 percent reduction in delay and 12 percent
modification in power consumption in compared with conventional
designs.
Abstract: Greenhouse gases (GHG) emissions impose major
threat to global warming potential (GWP). Unfortunately
manufacturing sector is one of the major sources that contribute
towards the rapid increase in greenhouse gases (GHG) emissions. In
manufacturing sector electric power consumption is the major driver
that influences CO2 emission. Titanium alloys are widely utilized in
aerospace, automotive and petrochemical sectors because of their
high strength to weight ratio and corrosion resistance. Titanium
alloys are termed as difficult to cut materials because of their poor
machinability rating. The present study analyzes energy consumption
during cutting with reference to material removal rate (MRR).
Surface roughness was also measured in order to optimize energy
consumption.
Abstract: In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.